Technology areas
Data and simulation
Demonstration, teleoperation for data collection, motion retargeting, robot datasets, data quality, physics simulation, synthetic data, digital twins, domain randomization, and sim-to-real transfer. The focus is data, environments, and tools for training and validation. Simulation used only to validate a new learning algorithm does not automatically qualify.
136 selected · 91 in the last 30 days
机器之心 · 微信公众号 ·
Tsinghua team builds HandsOn dexterous manipulation benchmark with 66 tasks to evaluate robot bimanual capabilities
Ding Ning's team at Tsinghua University, together with researchers from Beijing University of Posts and Telecommunications, Peking University, and Nature Will, built HandsOn, a simulation platform and evaluation benchmark for cross-embodiment dexterous manipulation, containing 66 manually verified tasks and 18,000 human simulation teleoperation demonstrations.
机器之心 · 微信公众号 ·
Harvard, Berkeley, NVIDIA and others propose RAX, using online exploration scaling to let robots learn skills with zero demonstrations
A research team from Harvard, NVIDIA, Berkeley, MIT and Stanford proposes RAX (Robot Agent eXploration), which connects a general coding agent to robot perception and control interfaces, uses online exploration to write successful decisions into executable programs and accumulate them as reusable skills, while keeping model parameters frozen.
HuggingFace Daily Papers ·
RynnVLA-Latent: Scaling robotic manipulation foundation models with 3D latent actions
The research team proposes the RynnVLA-Latent framework, which uses RynnLAM to learn continuous, 3D-grounded latent actions from visual changes without requiring native robot control signals. The method processes 30.1K hours of human, robot, and simulation video, generating 745.52M latent action descriptors, then uses flow matching to predict latent action chunks and adapt them to specific embodiments.
云深处科技 · 微信公众号 ·
DEEP Robotics unveils five embodied brain results: world model DR-WM-1.0, VLA model DR-VLA-2.0, and more
DEEP Robotics has released five research results centered on its self-developed embodied brain, DEEPRobotics-Brain, including the world model DR-WM-1.0, the embodied foundation model DR-VLA-2.0, the embodied agent DR-Agent, the policy optimization framework DR-APO, and the data closed-loop platform DR-Benchmark. The company is also collaborating with seven universities, including MIT, Tsinghua, and Zhejiang University.
Kinetix AI · YouTube ·
KAI Halo case study EgoWild2Dex: training bimanual dexterous manipulation with first-person data
The KAI Halo case study EgoWild2Dex shows how high-quality bimanual dexterous manipulation capabilities can be derived from highly challenging egocentric data. The project page is https://mmlab.hk/egowild2dex.
简智机器人 · X ·
Genrobot open-sources Gen-HumanWholeBody first-person whole-body manipulation dataset
Genrobot has released and open-sourced Gen-HumanWholeBody, a first-person whole-body manipulation dataset it says has the industry's highest precision, hosted on Hugging Face. The dataset contains 600 hours of whole-body manipulation data, approximately 3 cm whole-body MPJPE, 16,976 real-world scenes, and 1,281 human skills, and is open for research on whole-body motion learning, human-to-robot transfer, and embodied foundation models.
NEURA Robotics ·
NEURA Robotics unveils 4NE1 Gen 4 humanoid robot and opens TUM RoboGym with Technical University of Munich
NEURA Robotics and the Technical University of Munich (TUM) have opened TUM RoboGym at LabCampus near Munich Airport, covering more than 2,300 square meters. TUM MIRMI is a co-builder, the initial collaboration runs for three years, and the two parties are jointly investing about 17 million euros, of which NEURA is contributing about 11 million euros.
Xbotics具身智能实验室 · 微信公众号 ·
How to Choose a Robot Simulator: Same Success, Tenfold Contact Force Gap
The article interprets a simulator comparison report released by Manda Robotics in early October, running about ten sets of experiments with the same Franka 7-axis robotic arm and the same control program on four physics engines: PhysX, MuJoCo, MuJoCo Warp, and Genesis.
3D视觉工坊 · 微信公众号 ·
SenseTime and joint team evaluate GPT-6-Astra embodied capabilities, open-source SenseNova-RoboRSI framework and 27B model
A joint team including SenseTime and The Hong Kong University of Science and Technology (Guangzhou) released the report "Has GPT-6-Astra Achieved Embodied Intelligence?", systematically evaluating GPT-6-Astra's embodied capabilities across 12 benchmarks, and simultaneously open-sourced the SenseNova-RoboRSI evaluation framework and a 27B embodied model.
NVIDIA ·
NVIDIA Cosmos Expands with New Tools for Training, Evaluating and Deploying World Models
NVIDIA has expanded the Cosmos platform with new training tools, simulation checkpoints and Cosmos Data Factory blueprints for training, evaluating and deploying world models.
arXiv cs.RO ·
Learning from Fleet Experience: Collective Experience Learning Across 96 Robots
The paper proposes the Collective Experience Learning (CEL) paradigm, in which deployed robots pool their own execution experience to update a shared policy that is then returned to the fleet for use. It is implemented through failure-guided experience retrieval fine-tuning (FERT), which uses failure contexts to retrieve relevant segments from successful trajectories and prioritizes their recorded actions for supervised updates, without additional expert demonstrations or corrective actions; a supporting fault-tolerant asynchronous training system (FATS) coordinates robot execution, cloud inference, and policy optimization.
机器人前瞻 · 微信公众号 ·
NVIDIA open-sources robot data engine Flora, labeling cost about 1/125 that of GPT-6 Astra
NVIDIA released and open-sourced the data engine Flora, which converts raw robot video into training data such as timestamped action descriptions, process rewards, and outcome rewards; it is already used to train the GR00T series models. Flora consists of an action description model, a temporal segmentation model, and a reward model, fine-tuned from the Qwen3.5 series of vision-language models, and can label 200,000 hours of data per day on 512 GB300 GPUs.
NVIDIA ·
NVIDIA Expands Isaac Platform with New Humanoid Reference Platform, Isaac OS, and Isaac Lab 3.0
At GTC Berlin, NVIDIA announced an expansion of the Isaac open-source robotics development platform, adding the Isaac OS runtime, the officially released Isaac Lab 3.0 learning framework, and an open-source reference workflow based on DGX Station.
Xbotics具身智能实验室 · 微信公众号 ·
RLinf v0.4 released: open-source training framework upgrade for embodied reinforcement learning
RLinf, an open-source training framework for embodied reinforcement learning developed by Tsinghua University, Infinigence AI, and the Beijing Zhongguancun Academy, has officially released v0.4, with updates across four areas: a Lego-style real-machine system, real-machine post-training algorithms, full-modality model support, and a domestic computing power foundation.
Xbotics具身智能实验室 · 微信公众号 ·
Isaac Lab 3.0 released: multi-backend architecture, most workflows no longer require Isaac Sim installation
Isaac Lab 3.0 has been officially released, and the official recommendation is for new projects and projects migrating from 2.x to use v3.0.0 as their base. The new version adopts a multi-backend architecture with a unified task API, supporting backends such as Newton and OV Libraries. Supported tasks can switch physics, rendering, and visualization backends without rewriting logic, and most workflows do not require installing or launching Isaac Sim.
The Humanoid Hub ·
Ropedia releases open-world model W0, trained on about 10,000 hours of first-person human video
Ropedia released the open-world model W0, trained on about 10,000 hours of first-person human video. A single set of weights can predict the first-person view of humans, robotic arms, and humanoid robots (Unitree G1, Fourier GR-1), using a shared camera-plus-skeleton representation; adding a new robot requires only its URDF.
智源研究院 · 微信公众号 ·
BAAI's FlagOS 2.2 released: over 1,454 operators, 27% cross-chip performance gain
BAAI presented FlagOS 2.2 progress at the 2026 AI Open Computing Conference and FlagOS Technical Conference; the version was released on September 30. Public operators in the nine operator libraries rose from 564 to 1,454 (890 added). In tests covering over a thousand operators and 10 heterogeneous AI chips, cross-chip operator performance improved by about 27% over the previous version. The FlagOS-Compressor weight conversion and quantization tool was released for the first time, enabling a new model to be adapted to as many as 12 chips within one day.
自变量机器人 · 微信公众号 ·
X Square Robot releases X2Real simulation benchmark, with 0.96 correlation between simulated and real-robot task success rates
X Square Robot has released X2Real, an evolvable simulation evaluation benchmark. Its simulated evaluation and real-robot evaluation achieve a task success rate correlation of 0.96 and a progress score correlation of 0.99.
雷科技 ·
WorldOracle world-model evaluation platform launched, using real-robot testing to fact-check the industry
On October 16, WorldOracle, an action-driven world-model evaluation platform jointly completed by researchers from AgiBot, NVIDIA, Princeton University, the University of Texas at Austin, and the University of Toronto, was officially released, opening evaluation submissions to developers.
AI前线 · 微信公众号 ·
Google releases Gemini 4 Argon physical reasoning model, connecting the full robotics R&D chain
Google has released Gemini 4 (Argon), positioned as a general physical reasoning model focused on interaction with the physical world, covering the full robotics lifecycle from control execution and simulation reconstruction to data annotation and self-improvement. On the ERQA embodied reasoning benchmark, Argon scored 87%, surpassing Claude Opus 5.5 (82.3%) and GPT-6 Astra (81%); in the AA-Omniscience test, its hallucination rate was 15%, lower than the 51% and 59% of the latter two.